Spatial distribution of rare species in lotic habitats
Bibliographic record
Abstract
Abstract. Species rarity is a common phenomenon in the biological world. Although rare species have always interested biologists, the meaning of ‘rare’ has not always been clear with the definition of rarity often arbitrary. In the current study, we investigate rarity in stream ecosystems using black flies (Diptera: Simuliidae). We defined rare species a priori as those species found ≤ 10% of stream sites examined ( n = 111 streams for ‘summer collections’; n = 88 collection for ‘spring’ collections). Hence, we are exploring only one axis of rarity, restricted range. We first consider the distribution of each rare species separately to determine if the mean (euclidian) distance among streams (habitats) for each rare species differs from a random model. We next took a collective approach by pooling all rare species to determine the influence of stream conditions, niche breadth, and distance among habitats on rarity. Even within this biologically uniform group of flies, dispersal, range limits, and stream conditions all might play a role in rarity, and the importance of each of these factors appear to vary among species. Rather than looking for broad causes of rarity, future studies might be more fruitful if they looked at species‐specific causes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".